Meeting Ant Colony Optimization

Abstract

The ant system is a new meta-heuristic mainly for hard combinatorial optimization problems. It has been unexpectedly successful and known as ant colony optimization (ACO) in recent years. Nowadays, a series of improvements have been made to the ACO, most of which focus on the exploitation of gather information to guide the search of ant colony towards better solution space but neglect the exploration of new tours. In order to enlarge the ants' searching space and diversify the searching solutions, Meeting ACO is proposed here. The main strategy used in this new algorithm is to combine pairs of searching ants together to expand the diversification of the search. To make up the influence caused by limited number of meeting ants, a threshold constant is applied to make the algorithm function normally. As proved by the simulation experiments, the Meeting ACO is ranked among the best ACO for tackling the TSP problems.